David Hale Leidos preview Ineffective heuristic methods Ineffective at certain congestion levels Lack of accountability Low market share Competing technologies Heuristic methods ASCTs optimize complex networks in only a few seconds ID: 584893
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Slide1
Limitations of adaptive signals
David Hale (Leidos)Slide2
preview
Ineffective heuristic methodsIneffective at certain congestion levelsLack of accountability
Low market shareCompeting technologiesSlide3
Heuristic methods
ASCT’s optimize complex networks in only a few seconds.
Is this enough time to produce a good solution?Or, is it only enough time to produce a “quick and dirty” solution?Industrial engineering experts would not be impressed.
Fast Methods (not effective)
“
Equisat
”
Webster’s method
Greedy algorithmHill-climbingSlow Methods (effective)Simulated annealingEvolutionary algorithmsDerivative-free methodsSlide4
y
z
x
Run Time
Delay Reduction
A
B
CSlide5
Adapting vs. optimizing
(none)
Non-Adaptive,
Quasi-Adaptive
Fully Adaptive
Quick Optimization
Thorough OptimizationSlide6
Degree of saturation
“If geared toward sporadic demand, they’re effective. In corridors with defined peaks and aggressive timing, they experience diminishing returns.”
Delay
Degree of Saturation
0.80
1.00Slide7
accountability
“The industry needs a tool to quantify myriad adaptive products.”
“People are implementing these systems without a real analysis.”
Proprietary, secret algorithms
Capacity
analysis? NO
Simulation? DIFFICULT
Most products can’t do it
VISSIM API = extra $$$Too much time, money, expertiseSlide8
accountability
“
There is just way too much marketing.”Advertising
over
science?
Capitalism, good and bad
Cherry-picked case studies
67
% said ASCT was good for oversaturated conditionsLaw & OrderITE Community discussion on ASCTExperts with decades of signal experienceASCT is just “one tool in the toolbox”
ASCT “has its place”Slide9
Market share
“With less than 5% market share after 5 decades, acceptance is not consistent with successful technologies.”
“Adaptive control in its infancy?”Decades of availability (1960’s)
SCATS (1976), SCOOT (1981)
Fewer than 5% of signals are adaptive
Why?
Costs too high
Uncertainty about benefitsSlide10
Competing technologies
“Automated performance measures allow agencies to optimize and manage signals without an adaptive system.”
Data drivenQuasi-adaptive
Stronger algorithmsSlide11
Recent quotes
“The industry needs a tool to quantify myriad adaptive products.”
“People are implementing these systems without a real analysis.”“If geared toward sporadic demand, they’re effective. In corridors with defined peaks and aggressive timing, they experience diminishing returns.”
“We only use them when other options have failed.”
“There is just way too much marketing.”
“Clearly the jury is out on where they should be deployed.”
“From my experience it is smoke and mirrors.”
“With less than 5% market share after 5 decades, acceptance is not consistent with successful technologies.”
“Automated performance measures allow agencies to optimize and manage signals without an adaptive system.”Slide12
My current opinion
Traffic too light = not cost effective
Delay not sensitive below 80% saturationTraffic too heavy = not cost
effective
Everything is pre-timed over 120% saturation
No platoon progression
Cycle, offsets, phasing sequence insignificant
Traffic medium = sometimes cost effective
Sporadic demand (movie theater, football stadium)Unpredictable pedestrian activityEmergency vehiclesIncidents / accidentsSlide13
Limitations of adaptive signals
David Hale (Leidos)